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Genetic Algorithm for Feature Selection

version 1.1.0 (59.4 KB) by Jingwei Too
Simple algorithm shows how the genetic algorithm (GA) used in the feature selection problem.

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Updated 23 Jul 2020

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I provide a simple genetic algorithm (GA) for feature selection tasks, which can select the potential features to improve the classification accuracy.

The "Main" script illustrates the example of how GA can solve the feature selection problem using a benchmark data-set.

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Detail of GA can be found in the following papers:
[1] Too, J. and Abdullah, A.R., 2020. A new and fast rival genetic algorithm for feature selection. The Journal of Supercomputing.
DOI: https://doi.org/10.1007/s11227-020-03378-9

[2] Too, J., Abdullah, A.R., Mohd Saad, N. and Tee, W., 2019. EMG feature selection and classification using a Pbest-guide binary particle swarm optimization. Computation, 7(1), p.12.
DOI: https://doi.org/10.3390/computation7010012

Cite As

Too, Jingwei, and Abdul Rahim Abdullah. “A New and Fast Rival Genetic Algorithm for Feature Selection.” The Journal of Supercomputing, Springer Science and Business Media LLC, July 2020, doi:10.1007/s11227-020-03378-9.

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Too, Jingwei, et al. “EMG Feature Selection and Classification Using a Pbest-Guide Binary Particle Swarm Optimization.” Computation, vol. 7, no. 1, MDPI AG, Feb. 2019, p. 12, doi:10.3390/computation7010012.

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MATLAB Release Compatibility
Created with R2018a
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Genetic Algorithm for Feature Selection